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Volume 32 Issue 5
Oct 2021
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Jian Chen, Hideyuki O-tani, Tomohide Takeyama, Satoru Oishi, Hori Muneo Hori. A Probabilistic Liquefaction Hazard Assessment for Urban Regions Based on Dynamics Analysis Considering Soil Uncertainties. Journal of Earth Science, 2021, 32(5): 1129-1138. doi: 10.1007/s12583-021-1431-1
Citation: Jian Chen, Hideyuki O-tani, Tomohide Takeyama, Satoru Oishi, Hori Muneo Hori. A Probabilistic Liquefaction Hazard Assessment for Urban Regions Based on Dynamics Analysis Considering Soil Uncertainties. Journal of Earth Science, 2021, 32(5): 1129-1138. doi: 10.1007/s12583-021-1431-1

A Probabilistic Liquefaction Hazard Assessment for Urban Regions Based on Dynamics Analysis Considering Soil Uncertainties

doi: 10.1007/s12583-021-1431-1
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  • Corresponding author: Jian Chen, jchen@jamstec.go.jp
  • Received Date: 04 Dec 2020
  • Accepted Date: 03 Feb 2021
  • Publish Date: 01 Oct 2021
  • Earthquake induced liquefaction is one of the main geo-disasters threating urban regions, which not only causes direct damages to buildings, but also delays both real-time disaster relief actions and reconstruction activities. It is thus important to assess liquefaction hazard of urban regions effectively and efficiently for disaster prevention and mitigation. Conventional assessment approaches rely on engineering indices such as the factor of safety (FS) against liquefaction, which cannot take into account directly the uncertainties of soils. In contrast, a physics simulation-based approach, by solving soil dynamics problems coupled with excess pore water pressure (EPWP) it is possible to model the uncertainties directly via Monte Carlo simulations. In this study, we demonstrate the capability of such an approach for assessing an urban region with over 10 000 sites. The permeability parameters are assumed to follow a base-10-lognormal distribution among 100 model analyses for each site. A dynamic simulation is conducted for each model analysis to obtain the EPWP results. Based on over 1 million EPWP analysis models, we obtained a probabilistic liquefaction assessment. Empowered by high performance computing, we present for the first time a probabilistic liquefaction hazard assessment for urban regions based on dynamics analysis, which consider soil uncertainties.

     

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